Health and Environmental Co-Benefits of City Urban Form in Latin America: An Ecological Study
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Citações na Scopus
3
Tipo de produção
article
Data de publicação
2022
Título da Revista
ISSN da Revista
Título do Volume
Editora
MDPI
Autores
AVILA-PALENCIA, Ione
SANCHEZ, Brisa N.
RODRIGUEZ, Daniel A.
PEREZ-FERRER, Carolina
MIRANDA, J. Jaime
BILAL, Usama
USECHE, Andres F.
WILCHES-MOGOLLON, Maria A.
MOORE, Kari
Citação
SUSTAINABILITY, v.14, n.22, article ID 14715, 14p, 2022
Resumo
We investigated the association of urban landscape profiles with health and environmental outcomes, and whether those profiles are linked to environmental and health co-benefits. In this ecological study, we used data from 208 cities in 8 Latin American countries of the SALud URBana en America Latina (SALURBAL) project. Four urban landscape profiles were defined with metrics for the fragmentation, isolation, and shape of patches (contiguous area of urban development). Four environmental measures (lack of greenness, PM2.5, NO2, and carbon footprint), two cause-specific mortality rates (non-communicable diseases and unintentional injury mortality), and prevalence of three risk factors (hypertension, diabetes, and obesity) for adults were used as the main outcomes. We used linear regression models to evaluate the association of urban landscape profiles with environmental and health outcomes. In addition, we used finite mixture modeling to create co-benefit classes. Cities with the scattered pixels profile (low fragmentation, high isolation, and compact shaped patches) were most likely to have positive co-benefits. Profiles described as proximate stones (moderate fragmentation, moderate isolation, and irregular shape) and proximate inkblots (moderate-high fragmentation, moderate isolation, and complex shape) were most likely to have negative co-benefits. The contiguous large inkblots profile (low fragmentation, low isolation, and complex shape) was most likely to have mixed benefits.
Palavras-chave
cities, Latin America, population density, air pollution, green space, risk factors, co-benefits
Referências
- Andersen R, 2003, CAN J SOCIOL, V28, P584, DOI 10.2307/3341848
- [Anonymous], 2019, LANCET, V393, P2276, DOI 10.1016/S0140-6736(19)31323-6
- Bilal U, 2021, NAT MED, V27, P463, DOI 10.1038/s41591-020-01214-4
- Cervero R, 2013, J TRANSP LAND USE, V6, P7, DOI 10.5198/jtlu.v6i1.425
- Chandrabose M, 2019, OBES REV, V20, P41, DOI 10.1111/obr.12759
- dlr, GLOB URB FOOTPR
- Duque JC, 2019, LANDSCAPE URBAN PLAN, V191, DOI 10.1016/j.landurbplan.2019.103640
- Ene, 2012, FRAGSTATS V4 SPATIAL
- Giles-Corti B, 2016, LANCET, V388, P2912, DOI 10.1016/S0140-6736(16)30066-6
- Griffin BA, 2013, HEALTH PLACE, V20, P51, DOI 10.1016/j.healthplace.2012.11.003
- Herbert D., 1997, CITIES SPACE CITY PL, V3rd
- Irwin EG, 2007, P NATL ACAD SCI USA, V104, P20672, DOI 10.1073/pnas.0705527105
- Legrain A, 2015, TRANSPORT RES F-TRAF, V34, P141, DOI 10.1016/j.trf.2015.08.001
- Metz B., 2001, INTERGOVERNMENTAL PA
- Moran D, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aac72a
- Nieuwenhuijsen MJ, 2016, ENVIRON INT, V94, P251, DOI 10.1016/j.envint.2016.05.032
- Nieuwenhuijsen MJ, 2016, ENVIRON HEALTH-GLOB, V15, DOI 10.1186/s12940-016-0108-1
- Novaco R.W., 2009, TECHNOLOGY PSYCHOL W
- Quick H, 2020, EPIDEMIOLOGY, V31, P15, DOI 10.1097/EDE.0000000000001118
- Quistberg DA, 2019, J URBAN HEALTH, V96, P311, DOI 10.1007/s11524-018-00326-0
- Sallis JF, 2016, LANCET, V387, P2207, DOI 10.1016/S0140-6736(15)01284-2
- Sarmiento OL, 2021, PLOS ONE, V16, DOI 10.1371/journal.pone.0257528
- UN-WUP, 2018, WORLD URB PROSP, V12
- Weller BE, 2020, J BLACK PSYCHOL, V46, P287, DOI 10.1177/0095798420930932
- WHO, 2011, HLTH GREEN EC HLTH C
- World Health Organization, GLOB HLTH EST 2016 D